Use of a Self-guided Computerized Cognitive Behavioral Tool During COVID-19: Evaluation Study
Bibliographic record
Abstract
BACKGROUND: Internet-based programs can help provide accessible and inexpensive behavioral health care to those in need; however, the evaluation of these interventions has been mostly limited to controlled trials. Data regarding patterns of use and effectiveness of self-referred, open-access online interventions are lacking. We evaluated an online-based treatment designed to address stress, depression, and conflict management, the Dartmouth PATH Program, in a freely available and self-guided format during the COVID-19 pandemic. OBJECTIVE: The primary aim is to determine users' levels of stress and depression, and the nature of problems and triggers they reported during the COVID-19 pandemic. A secondary objective is to assess the acceptability and usability of the PATH content and determine whether such a program would be useful as a stand-alone open-access resource. The final objective is understanding the high dropout rates associated with online behavioral programs by contrasting the use pattern and program efficacy of individuals who completed session one and did not return to the program with those who came back to complete more sessions. METHODS: Cumulative anonymous data from 562 individuals were analyzed. Stress triggers, stress responses, and reported problems were analyzed using qualitative analysis techniques. Scores on usability and acceptability questionnaires were evaluated using the sign test and Wilcoxon signed rank test. Mixed-effects linear modeling was used to evaluate changes in stress and depression over time. RESULTS: A total of 2484 users registered from April through October 2020, most of whom created an account without initiating a module. A total of 562 individuals started the program and were considered in the data analysis. The most common stress triggers individuals reported involved either conflicts with family or spouses and work or workload. The most common problems addressed in the mood module were worry, anxiousness, or stress and difficulty concentrating or procrastination. The attrition rate was high with 13% (21/156) completing the conflict module, 17% (50/289) completing session one of the mood module, and 14% (16/117) completing session one of the stress module. Usability and acceptability scores for the mood and stress modules were significantly better than average. In those who returned to complete sessions, symptoms of stress showed a significant improvement over time (P=.03), and there was a significant decrease in depressive symptoms over all time points (P=.01). Depression severity decreased on average by 20% (SD 35.2%; P=.60) between sessions one and two. CONCLUSIONS: Conflicts with others, worry, and difficulty concentrating were some of the most common problems people used the programs to address. Individuals who completed the modules indicated improvements in self-reported stress and depression symptoms. Users also found the modules to be effective and rated the program highly for usability and acceptability. Nevertheless, the attrition rate was very high, as has been found with other freely available online-based interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT02726061; https://clinicaltrials.gov/ct2/show/NCT02726061.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".